A Study of Fraud Types, Challenges and Detection Approaches in Telecommunication
محورهای موضوعی : Machine learning
Kasra Babaei
1
( University of Nottingham Malaysia)
ZhiYuan Chen
2
( University of Nottingham Malaysia)
Tomas Maul
3
( University of Nottingham Malaysia)
کلید واژه: Fraud Detection, , Machine Learning, , Telecommunication, ,
چکیده مقاله :
Fraudulent activities have been rising globally resulting companies losing billions of dollars that can cause severe financial damages. Various approaches have been proposed by researchers in different applications. Studying these approaches can help us obtain a better understanding of the problem. The aim of this paper is to investigate different aspects of fraud prevention and detection in telecommunication. This study presents a review of different fraud categories in telecommunication, the challenges that hinder the detection process, and some proposed solutions to overcome them. Also, the performance of some of the state-of-the-art approaches is reported followed by our guideline and recommendation in choosing the best metrics.
Fraudulent activities have been rising globally resulting companies losing billions of dollars that can cause severe financial damages. Various approaches have been proposed by researchers in different applications. Studying these approaches can help us obtain a better understanding of the problem. The aim of this paper is to investigate different aspects of fraud prevention and detection in telecommunication. This study presents a review of different fraud categories in telecommunication, the challenges that hinder the detection process, and some proposed solutions to overcome them. Also, the performance of some of the state-of-the-art approaches is reported followed by our guideline and recommendation in choosing the best metrics.
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